Publications - 2017

2017

• 1. Anderson, A.B., "Concepts and computational methods for the electrochemical interface and applications: Past, present, and future", Current Opinion in Electrochemistry, 1(1):27-33, 2017 doi:10.1016/j.coelec.2016.12.010

  2. Melin, BS., Barnholtz-Sloan, JS., Wrensch, MR., Johansen, C., Il'yasova, D., Kinnersley, B., Ostrom, QT., Labreche, K., Chen, Y., Armstrong, G., Liu, Y., Eckel-Passow, JE., Decker, PA., Labussière, M., Idbaih, A., Hoang-Xuan, K., AL, D.S., Mokhtari, K., Delattre, JY., Broderick, P., Galan, P., Gousias, K., Schramm, J., Schoemaker, MJ., Fleming, SJ., Herms, S., Heilmann, S., Nöthen, MM., Wichmann, HE., Schreiber, S., Swerdlow, A., Lathrop, M., Simon, M., Sanson, M., Andersson, U., Rajaraman, P., Chanock, S., Linet, M., Wang, Z., Yeager, M., Consortium., G., Wiencke, JK., Hansen, H., McCoy, L., Rice, T., Kosel, ML., Sicotte, H., Amos, CI., Bernstein, JL., Davis, F., Lachance, D., Lau, C., Merrell, RT., Shildkraut, J., Ali-Osman, F., Sadetzki, S., Scheurer, M., Shete, S., Lai, RK., Claus, EB., Olson, SH., Jenkins, RB., Houlston, RS., Bondy, ML., "Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors.", Nat Genet, 49(5):789-794, 2017 doi:10.1038/ng.3823 PMID:28346443

  3. Chen, A., Liu, Y., Williams, S.M., Morris, N., Buchner, D.A., "Widespread epistasis regulates glucose homeostasis and gene expression", PLOS Genetics, 13(9):e1007025, 2017 doi:10.1371/journal.pgen.1007025

  4. McColl, K., Wildey, G., Sakre, N., Lipka, MB., Behtaj, M., Kresak, A., Chen, Y., Yang, M., Velcheti, V., Fu, P., Dowlati, A., "Reciprocal expression of INSM1 and YAP1 defines subgroups in small cell lung cancer.", Oncotarget, 8(43):73745-73756, 2017 doi:10.18632/oncotarget.20572 PMID:29088741

  5. Feng, Z., Wang, Z., Guo, Z., Zhou, W., Cai, Z., Durand, D.M., "High frequency stimulation of afferent fibers generates asynchronous firing in the downstream neurons in hippocampus through partial block of axonal conduction", Brain Research, 1661:67-78, 2017 doi:10.1016/j.brainres.2017.02.008

  6. McCallum, G.A., Sui, X., Qiu, C., Marmerstein, J., Zheng, Y., Eggers, T.E., Hu, C., Dai, L., Durand, D.M., "Chronic interfacing with the autonomic nervous system using carbon nanotube (CNT) yarn electrodes", Scientific Reports, 7(1):11723, 2017 doi:10.1038/s41598-017-10639-w

  7. Eggers, TE., Dweiri, YM., McCallum, GA., Durand, DM., "Model-based Bayesian signal extraction algorithm for peripheral nerves.", J Neural Eng, 14(5):056009-056009, 2017 doi:10.1088/1741-2552/aa7d94 PMID:28675376

  8. Liang, J., Le, TH., Edwards, DRV., Tayo, BO., Gaulton, KJ., Smith, JA., Lu, Y., Jensen, RA., Chen, G., Yanek, LR., Schwander, K., Tajuddin, SM., Sofer, T., Kim, W., Kayima, J., McKenzie, CA., Fox, E., Nalls, MA., Young, JH., Sun, YV., Lane, JM., Cechova, S., Zhou, J., Tang, H., Fornage, M., Musani, SK., Wang, H., Lee, J., Adeyemo, A., Dreisbach, AW., Forrester, T., Chu, PL., Cappola, A., Evans, MK., Morrison, AC., Martin, LW., Wiggins, KL., Hui, Q., Zhao, W., Jackson, RD., Ware, EB., Faul, JD., Reiner, AP., Bray, M., Denny, JC., Mosley, TH., Palmas, W., Guo, X., Papanicolaou, GJ., Penman, AD., Polak, JF., Rice, K., Taylor, KD., Boerwinkle, E., Bottinger, EP., Liu, K., Risch, N., Hunt, SC., Kooperberg, C., Zonderman, AB., Laurie, CC., Becker, DM., Cai, J., Loos, RJF., Psaty, BM., Weir, DR., Kardia, SLR., Arnett, DK., Won, S., Edwards, TL., Redline, S., Cooper, RS., Rao, DC., Rotter, JI., Rotimi, C., Levy, D., Chakravarti, A., Zhu, X., Franceschini, N., "Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.", PLoS Genet, 13(5), 2017 doi:10.1371/journal.pgen.1006728 PMID:28498854

  9. Paudel, T.R., Lambrecht, W.R.L., "Erratum: First-principles calculations of elasticity, polarization-related properties, and nonlinear optical coefficients in Zn-IV-N2 compounds [Phys. Rev. B 79, 245205 (2009)]", Physical Review B, 96(7):079906, 2017 doi:https://link.aps.org/doi/10.1103/PhysRevB.96.079906

  10. Skachkov, D., Lambrecht, W.R.L., "Native interstitial defects in ZnGeN2", Physical Review Materials, 1(5):054604, 2017 doi:https://link.aps.org/doi/10.1103/PhysRevMaterials.1.054604

  11. Baig, T., Amin, A.A., Deissler, R.J., Sabri, L., Poole, C., Brown, R.W., Tomsic, M., Doll, D., Rindfleisch, M., Peng, X., Mendris, R., Akkus, O., Sumption, M., Martens, M., "Conceptual designs of conduction cooled MgB 2 magnets for 1.5 and 3.0 T full body MRI systems", Superconductor Science and Technology, 30(4):043002, 2017 [link]

  12. Poole, C., Baig, T., Deissler, R.J., Martens, M., "Numerical analysis of the coupling loss induced quench protection for a 1.5 T whole-body MgB 2 MRI", Superconductor Science and Technology, 30(10):105005, 2017 [link]

  13. Gorelenkova Miller, O., Mieyal, J.J., "Critical Roles of Glutaredoxin in Brain Cells—Implications for Parkinson's Disease", Antioxidants & Redox Signaling, 2017 doi:10.1089/ars.2017.7411

  14. Miller, TE., Liau, BB., Wallace, LC., Morton, AR., Xie, Q., Dixit, D., Factor, DC., Kim, LJY., Morrow, JJ., Wu, Q., Mack, SC., Hubert, CG., Gillespie, SM., Flavahan, WA., Hoffmann, T., Thummalapalli, R., Hemann, MT., Paddison, PJ., Horbinski, CM., Zuber, J., Scacheri, PC., Bernstein, BE., Tesar, PJ., Rich, JN., "Transcription elongation factors represent in vivo cancer dependencies in glioblastoma.", Nature, 547(7663):355-359, 2017 doi:10.1038/nature23000 PMID:28678782

  15. Cohen, AJ., Saiakhova, A., Corradin, O., Luppino, JM., Lovrenert, K., Bartels, CF., Morrow, JJ., Mack, SC., Dhillon, G., Beard, L., Myeroff, L., Kalady, MF., Willis, J., Bradner, JE., Keri, RA., Berger, NA., Pruett-Miller, SM., Markowitz, SD., Scacheri, PC., "Hotspots of aberrant enhancer activity punctuate the colorectal cancer epigenome.", Nat Commun, 8:14400-14400, 2017 doi:10.1038/ncomms14400 PMID:28169291

  16. Rose, J., Homa, L., Meropol, S.B., Debanne, S.M., Bielefeld, R., Hoyen, C., Singer, M.E., "Health impact and cost-effectiveness of a domestically-produced rotavirus vaccine in India: A model based analysis", PLOS ONE, 12(11):e0187446, 2017 doi:10.1371/journal.pone.0187446

  17. Giblin, J.T., Jr., Mertens, J.B., Starkman, G.D., "A cosmologically motivated reference formulation of numerical relativity", Classical and Quantum Gravity, 34(21):214001, 2017 doi:10.1088/1361-6382/aa8af9

  18. Giblin, J.T., Mertens, J.B., Starkman, G.D., Zentner, A.R., "General relativistic corrections to the weak lensing convergence power spectrum", Physical Review D, 96(10):103530, 2017 doi:https://link.aps.org/doi/10.1103/PhysRevD.96.103530

  19. Li, X., Redline, S., Zhang, X., Williams, S., Zhu, X., "Height associated variants demonstrate assortative mating in human populations.", Sci Rep, 7(1):15689-15689, 2017 doi:10.1038/s41598-017-15864-x PMID:29146993

  20. He, KY., Wang, H., Cade, BE., Nandakumar, P., Giri, A., Ware, EB., Haessler, J., Liang, J., Smith, JA., Franceschini, N., Le, TH., Kooperberg, C., Edwards, TL., Kardia, SL., Lin, X., Chakravarti, A., Redline, S., Zhu, X., "Rare variants in fox-1 homolog A (RBFOX1) are associated with lower blood pressure.", PLoS Genet, 13(3), 2017 doi:10.1371/journal.pgen.1006678 PMID:28346479

  21. Sahni, J.M., Gayle, S.S., Webb, B.M., Weber-Bonk, K.L., Seachrist, D.D., Singh, S., Sizemore, S.T., Restrepo, N.A., Bebek, G., Scacheri, P.C., Varadan, V., Summers, M.K., and Keri, R.A. 2017. Mitotic vulnerability in triple-negative breast cancer associated with LIN9 is targetable with BET inhibitors. Cancer Research, 77:5395-5408.

  22. M. Zhao and A. B. Anderson, Predicting the Double Layer Width on Pt(111) in Acid and Base with Theory and Extracting It from Experimental Voltammograms, J. Phys Chem. C 121, 28051-28064 (2017).

  23. M. Zhao and A. B. Anderson, Theory of Hydrogen Deposition and Evolution on Cu(111) Electrodes, Journal of The Electrochemical Society, 164 (9) H691-H695 (2017).

  24. Walter R. L. Lambrecht, Churna Bhandari, and Mark van Schilfgaarde, Lattice polarization effects on the screened Coulomb interaction W of the GW approximation, Phys. Rev. Materials 1, 043802 (2017).

  25. Cheng Lu, James S. Lewis Jr.*, William D. Dupont, W. Dale Plummer Jr., Andrew Janowczyk, Anant Madabhushi*，“An Oral Cavity Squamous Cell Carcinoma Quantitative Histomorphometric-Based Image Classifier (OHbIC) of Nuclear Morphology Can Risk Stratify Patients for Disease Specific Survival”, Modern Pathology. 2017 Aug 4. doi: 10.1038/modpathol.2017.98

  26. Cheng Lu, Monica Khunger, Rajat Thawani, Vamsidhar Velcheti, Anant Madabhushi*, Computer extracted measurements of intra-tumoral heterogeneity on H&E stained tissue images to distinguish short term and long term survivors in patients with non-small cell lung carcinoma. ASCO 2017.

  27. Cheng Lu, James Lewis Jr., Anant Madabhushi*, Computer extracted features of nuclear architecture in H&E sections predicts disease specific survival in oral cavity squamous cell carcinoma patients. USCAP. San Antonio, USA, 2017.

  28. Brister, M. M.; Piñero-Santiago, L. E.; Morel, M.; Arce, R.; Crespo-Hernández, C. E. Photochemical Relaxation Pathways in Dinitropyrene Isomer Pollutants. J. Phys. Chem. A 2017, 121, 8197–8206.

  29. Dazard JE, Ishwaran H, Mehlotra R, Weinberg A, Zimmerman P. Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting. Stat Appl Genet Mol Biol. 2018 February 17; 17(1): . doi:10.1515/sagmb-2017-0038.

  30. Veliz FA, Ma Y, Molugu SK, Tiu BDB, Stewart PL, French RH, Steinmetz NF. Photon management through virus-programmed supramolecular arrays. (2017) Advanced Biosystems, 1:170008.

  31. Rachel Morrison; Jennifer Carter; Saryu Fensin, "Exploring the Interactions between Grain Boundaries and Precipitates in Ni-Al Using Molecular Dynamics", Interfaces, Grain Boundaries and Surfaces from Atomistic and Macroscopic Approaches – Interface Kinetics II, MS&T 2017. 

  32. Pasquale LR, Aschard H, Kang JH, Bailey JN, Lindström S, Chasman DI, Christen WG, Allingham RR, Ashley-Koch A, Lee RK, Moroi SE, Brilliant MH, Wollstein G, Schuman JS, Fingert J, Budenz DL, Realini T, Gaasterland T, Gaasterland D, Scott WK, Singh K, Sit AJ, Igo RP Jr, Song YE, Hark L, Ritch R, Rhee DJ, Gulati V, Havens S, Vollrath D, Zack DJ, Medeiros F, Weinreb RN, Pericak-Vance MA, Liu Y, Kraft P, Richards JE, Rosner BA, Hauser MA, Haines JL, Wiggs JL. Age at natural menopause genetic risk score in relation to age at natural menopause and primary open-angle glaucoma in a US-based sample. Menopause. 2017 Feb;24(2):150-156. doi: 10.1097/GME.0000000000000741.

  33. Aung T, Ozaki M, Lee MC, Schlötzer-Schrehardt U, Thorleifsson G, Mizoguchi T, Igo RP Jr, Haripriya A, Williams SE, Astakhov YS, Orr AC, Burdon KP, Nakano S, Mori K, Abu-Amero K, Hauser M, Li Z, Prakadeeswari G, Bailey JNC, Cherecheanu AP, Kang JH, Nelson S, Hayashi K, Manabe SI, Kazama S, Zarnowski T, Inoue K, Irkec M, Coca-Prados M, Sugiyama K, Järvelä I, Schlottmann P, Lerner SF, Lamari H, Nilgün Y, Bikbov M, Park KH, Cha SC, Yamashiro K, Zenteno JC, Jonas JB, Kumar RS, Perera SA, Chan ASY, Kobakhidze N, George R, Vijaya L, Do T, Edward DP, de Juan Marcos L, Pakravan M, Moghimi S, Ideta R, Bach-Holm D, Kappelgaard P, Wirostko B, Thomas S, Gaston D, Bedard K, Greer WL, Yang Z, Chen X, Huang L, Sang J, Jia H, Jia L, Qiao C, Zhang H, Liu X, Zhao B, Wang YX, Xu L, Leruez S, Reynier P, Chichua G, Tabagari S, Uebe S, Zenkel M, Berner D, Mossböck G, Weisschuh N, Hoja U, Welge-Luessen UC, Mardin C, Founti P, Chatzikyriakidou A, Pappas T, Anastasopoulos E, Lambropoulos A, Ghosh A, Shetty R, Porporato N, Saravanan V, Venkatesh R, Shivkumar C, Kalpana N, Sarangapani S, Kanavi MR, Beni AN, Yazdani S, Lashay A, Naderifar H, Khatibi N, Fea A, Lavia C, Dallorto L, Rolle T, Frezzotti P, Paoli D, Salvi E, Manunta P, Mori Y, Miyata K, Higashide T, Chihara E, Ishiko S, Yoshida A, Yanagi M, Kiuchi Y, Ohashi T, Sakurai T, Sugimoto T, Chuman H, Aihara M, Inatani M, Miyake M, Gotoh N, Matsuda F, Yoshimura N, Ikeda Y, Ueno M, Sotozono C, Jeoung JW, Sagong M, Park KH, Ahn J, Cruz-Aguilar M, Ezzouhairi SM, Rafei A, Chong YF, Ng XY, Goh SR, Chen Y, Yong VHK, Khan MI, Olawoye OO, Ashaye AO, Ugbede I, Onakoya A, Kizor-Akaraiwe N, Teekhasaenee C, Suwan Y, Supakontanasan W, Okeke S, Uche NJ, Asimadu I, Ayub H, Akhtar F, Kosior-Jarecka E, Lukasik U, Lischinsky I, Castro V, Grossmann RP, Megevand GS, Roy S, Dervan E, Silke E, Rao A, Sahay P, Fornero P, Cuello O, Sivori D, Zompa T, Mills RA, Souzeau E, Mitchell P, Wang JJ, Hewitt AW, Coote M, Crowston JG, Astakhov SY, Akopov EL, Emelyanov A, Vysochinskaya V, Kazakbaeva G, Fayzrakhmanov R, Al-Obeidan SA, Owaidhah O, Aljasim LA, Chowbay B, Foo JN, Soh RQ, Sim KS, Xie Z, Cheong AWO, Mok SQ, Soo HM, Chen XY, Peh SQ, Heng KK, Husain R, Ho SL, Hillmer AM, Cheng CY, Escudero-Domínguez FA, González-Sarmiento R, Martinon-Torres F, Salas A, Pathanapitoon K, Hansapinyo L, Wanichwecharugruang B, Kitnarong N, Sakuntabhai A, Nguyn HX, Nguyn GTT, Nguyn TV, Zenz W, Binder A, Klobassa DS, Hibberd ML, Davila S, Herms S, Nöthen MM, Moebus S, Rautenbach RM, Ziskind A, Carmichael TR, Ramsay M, Álvarez L, García M, González-Iglesias H, Rodríguez-Calvo PP, Fernández-Vega Cueto L, Oguz Ç, Tamcelik N, Atalay E, Batu B, Aktas D, Kasım B, Wilson MR, Coleman AL, Liu Y, Challa P, Herndon L, Kuchtey RW, Kuchtey J, Curtin K, Chaya CJ, Crandall A, Zangwill LM, Wong TY, Nakano M, Kinoshita S, den Hollander AI, Vesti E, Fingert JH, Lee RK, Sit AJ, Shingleton BJ, Wang N, Cusi D, Qamar R, Kraft P, Pericak-Vance MA, Raychaudhuri S, Heegaard S, Kivelä T, Reis A, Kruse FE, Weinreb RN, Pasquale LR, Haines JL, Thorsteinsdottir U, Jonasson F, Allingham RR, Milea D, Ritch R, Kubota T, Tashiro K, Vithana EN, Micheal S, Topouzis F, Craig JE, Dubina M, Sundaresan P, Stefansson K, Wiggs JL, Pasutto F, Khor CC. Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci. Nat Genet. 2017 Jul;49(7):993-1004. doi: 10.1038/ng.3875. Epub 2017 May 29. PMID: 28553957

  34. Kunkle BW, Vardarajan BN, Naj AC, Whitehead PL, Rolati S, Slifer S, Carney RM, Cuccaro ML, Vance JM, Gilbert JR, Wang LS, Farrer LA, Reitz C, Haines JL, Beecham GW, Martin ER, Schellenberg GD, Mayeux RP, Pericak-Vance MA. Early-Onset Alzheimer Disease and Candidate Risk Genes Involved in Endolysosomal Transport. JAMA Neurol. 2017 Sep 1;74(9):1113-1122. doi: 10.1001/jamaneurol.2017.1518.

  35. Jiankui Yuan, Mitchell Machtay, A Monte Carlo model and its commissioning for the Leksell Gamma Knife Perfexion radiosurgery system, Medical Phyisics, Vol. 44, 4910-4918 (2017).

  36. Grandhi S, Bosworth C, Maddox W, Sensiba C, Akhavanfard S, Ni Y, LaFramboise T (2017). Loss of Selective Constraints Drives Damage to Mitochondrial Genomes in Cancer. Human Molecular Genetics 2017 May 5. doi: 10.1093/hmg/ddx172

  37. Bosworth C, Grandhi S, Gould MP, LaFramboise T (2017). Detection and Quantification of Mitochondrial DNA Deletions from Next Generation Sequence Data. BMC Bioinformatics (in press). 

  38. Cyncynates, D., Chiel, J., Sidhu, J. and Starkman, G.D., 2017. Reconsidering seismological constraints on the available parameter space of macroscopic dark matter. Physical Review D, 95(6), p.063006.

  39. Pitek AS, Wang Y, Gulati S, Gao H, Stewart PL, Simon DI, Steinmetz NF. Elongated plant virus-based nanoparticles for enhanced delivery of thrombolytic therapies. 2017 Molecular Pharmaceutics, 14:3815-3823.

  40. Lingshuang Song, Lin Yang, Jie Meng, and Sichun Yang, Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental-Computational Study, Journal of Physical Chemistry Letters 8 347–351 (2017)

  41. Martin Gustavsson, Liwen Wang, Noortje van Gils, Bryan S. Stephens, Penglie Zhang, Thomas J. Schall, Sichun Yang, Ruben Abagyan, Mark R. Chance, Irina Kufareva, and Tracy M. Handel, Structural basis of ligand interaction with atypical chemokine receptor 3, Nature Communications 8 14125 (2017) 

  42. Lee PW, Isarov SA, Wallat JD, Molugu SK, Shukla S, Sun JEP, Zhang J, Zheng Y, Lucius Dougherty M, Konkolewicz D, Stewart PL, Steinmetz NF, Hore MJA, Pokorski JK. (2017) Polymer structure and conformation alters antigenicity of virus-like particle-polymer conjugates. JACS, 139 (9):3312–3315. (JACS Spotlights Article and Cover article) 

  43. Gulati NM, Pitek AS, Steinmetz NF, Stewart PL. Cryo-electron tomography investigation of serum albumin-camouflaged tobacco mosaic virus nanoparticles. (2017)  Nanoscale,  9:3408-3415, DOI: 10.1039/C6NR06948G.

  44. Jiayuan Miao, Mesfin Tsige, and Philip L. Taylor. "Generalized model for the diffusion of solvents in glassy polymers: From Fickian to Super Case II." Journal of Chemical Physics 147 (2017): 044904. 

  45. Jiayuan Miao, Darrell H. Reneker, Mesfin Tsige, and Philip L. Taylor. "Molecular dynamics simulations and morphology analysis of TEM imaged PVDF nanofibers." Polymer 125 (2017): 190-199

  46. Quasiparticle self-consistent GW electronic band structure of Cd-IV-N2 compounds, Sai Lyu and Walter R. L. Lambrecht, Phys. Rev. Materials 1, 024606 (2017)

  47. Zone-center phonons in yellow phase CsSnI3, Ling-yi Huang and Walter R. L. Lambrecht, Phys. Rev. Materials 1, 024601 (2017)

  48. Charlie Y. Wang, Yuchi Liu, Shuying Huang, Mark A. Griswold, Nicole Seiberlich, Xin Yu, "P magnetic resonance fingerprinting for rapid quantification of creatine kinase reaction rate in vivo", NMR in Biomedicine 2017 (accepted in 12, July 2017).

  49. Howell B, McIntyre CC, Role of Soft-Tissue Heterogeneity in Computational Models of Deep Brain Stimulation, Brain Stimul. 2017 Jan - Feb;10(1):46-50. doi: 10.1016/j.brs.2016.09.001. Epub 2016 Sep 8.

  50. Gunalan K, Chaturvedi A, Howell B, Duchin Y, Lempka SF, Patriat R, Sapiro G, Harel N, McIntyre CC, Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example, PLoS One. 2017 Apr 25;12(4):e0176132. doi: 10.1371/journal.pone.0176132. eCollection 2017.

  51. Ashwood, B.; Ortiz-Rodríguez, L. A.; Crespo-Hernández, C. E. "Excited-State Dynamics of O6-Methylguanosine: Impact of O6-Methylation on the Photophysics of Guanine Monomers", J. Phys. Chem. Lett. 2017, 8, 4380–4385.

  52. Ashwood, B.; Jockusch, S.; Crespo-Hernández, C. E. "Excited-State Dynamics of the Thiopurine Prodrug 6-Thioguanine: Can N9-Glycosylation Affects Its Phototoxic Activity?", Molecules 2017, 22, 379

  53. Ashwood, B.; Jockusch, S.; Crespo-Hernández, C. E. "Photochemical Reactivity of dTPT3: A Crucial Nucleobase Derivative in the Development of Semi-Synthetic Organisms", J. Phys. Chem. Lett. 2017, 8, 2387−2392.

  54. R. DiScipio, C. E. Crespo-Hernández, “The Energetic Journey of UV Light Through Biomolecular Pterin,” Cleveland Section of the American Chemical Society: Meeting in Miniature, Cleveland State University, Cleveland, Ohio, March 13, 2017. (O)

  55. R. DiScipio, C. E. Crespo-Hernández, “Ultrafast Reactive Species Generation in Pterin Biomolecules,” Cleveland Section of the American Chemical Society: GO Chem, Kalahari Resorts, Sandusky, Ohio, February 25, 2017. (O) 

  56. Eric W. Blanton, Mark Hagemann, Keliang He, Jie Shan, Walter R. L. Lambrecht, Raman study of the vibrational modes in ZnGeN2 (0001), Journal of Applied Physics 121, 055704 (2017) 

  57. Liqun Zhang, Matthias Buck,” Molecular Dynamics Simulations Reveal Isoform Specific Contact Dynamics Between the Plexin Rho GTPase Binding Domain (RBD) and Small Rho GTPases Rac1 and Rnd1”. J. Phys. Chem. B.DOI: 10.1021/acs.jpcb.6b11022. 2017. 

  58. Turner, Mark. 2017.  “Multimodal Form-Meaning Pairs for Blended Classic Joint Attention.” Linguistics Vanguard. 

  59. Bucheli, DR, Janowczyk, A, Gilmore, H, Romero, E, Madabhushi, A, “A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in Estrogen Receptor Positive Breast Cancers”, Cytometry A. 2017 Feb 13. doi: 10.1002/cyto.a.23065. [Epub ahead of print] (PMID: 28192639). 

  60. Rusu, M, Purysko, A, Verma, S, Kiechle, J, Gollamudi, J, Ghose, S, Herrmann, K, Gulani, V, Paspulati, R, Ponsky, L, Böhm, M, Haynes, A-M, Moses, D, Shnier, R, Delprado, W, Thompson, J, Stricker, P, and Madabhushi, A, “Computational imaging reveals shape differences between normal and malignant prostates on MRI”, Sci Rep. 2017 Feb 1;7:41261. doi: 10.1038/srep41261. (PMID: 28145532).

  61. Rusu, M, Prabhakar, R, Gilkeson, R, Yang, M, Donatelli, C, Thawani, R, Jacono, F, Linden, P, Madabhushi, A, “Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study”, European Radiology, In Press. 

  62. Corredor, G, Whitney, J, Arias, V, Madabhushi, A, Romero, E, “Training a cell level classifier for detecting basal cell carcinoma by combining human visual attention maps with low level handcrafted features”, Journal of Medical Imaging, Accepted. 

  63. Xu, J, Monaco, J, Sparks, R, Madabhushi, A, “Connecting Markov Random Fields and Active Contour Models: Application to Gland Segmentation and Classification”, Journal of Medical Imaging, Accepted. 

  64. Alilou, M, Beig, N, Oroji, M, Prabhakar, R, Velcheti, V, Rakshit, S, Reddy, N, Yang, M, Jacono, F, Gilkeson, R, Linden, P, Madabhushi, A, “An integrated segmentation and shape based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT”, Medical Physics, Accepted.

  65. Viswanath, S, Tiwari, P, Lee, G, Madabhushi, A, Alzheimer’s Disease Neuroimaging Initiative. “Dimensionality Reduction-based Fusion Approaches for Imaging and Non-imaging Biomedical Data: Concepts, Workflow, and Use-Cases”, BMC Medical Imaging, 2017 Jan 5;17(1):2. doi: 10.1186/s12880-016-0172-6. (PMID: 28056889) [PubMed - in process]. 

  66. Lee, G, Veltri, R, Ali, S, Epstein, JI, Madabhushi, A, “Nuclear Shape and Architecture in Benign Fields Appear to Predict Biochemical Recurrence in Prostate Cancer Patients Following Radical Prostatectomy: Preliminary Findings”, European Urology Focus, In Press. 

  67. Ma D, Coppo S, Chen Y, McGivney DF, Jiang Y, Pahwa S, Gulani V, Griswold MA. Slice profile and B1 correction in 2D magnetic resonance fingerprinting. Magn. Reson. Med. 2017, Jan 11. doi:10.1002/mrm.26580. 

  68. Y. Li and Y.-T. T. Liao: Thermogravimetric analysis and modeling of NOMEX fabric pyrolysis, 10th US National Combustion Meeting, College Park, MD, April 23-26, 2017. C. Li and Y.-T. T. Liao: Transient flame growth and spread processes over thin solids in concurrent low-speed flows in microgravity – a comparison between large and small sample sizes, 10th US National Combustion Meeting, College Park, MD, April 23-26, 2017. 

  69. X.  Zhao, Y.-T. T. Liao, M. C. Johnston, J. S. T’ien, P. V. Ferkul, and S. L. Olson: Concurrent Flame Growth, Spread, and Quenching over Composite Fabric Samples in Low Speed Purely Forced Flow in Microgravity, Proceedings of the Combustion Institute, Vol. 36, pp. 2971-2978, 2017 

  70. Yu Wang, Lucas Fridman, Roger H. French, and Laura S. Bruckman, “Degradation Models of Photovoltaic Module Backsheets Exposed to Diverse Real World Condition,” Jun-2017.

  71. Yu Wang, Lucas Fridman, Roger French, and Laura S. Bruckman, “Stress/ Response Degradation Model of Photovoltaic Modules Exposed in Different Climatic Zones,” 31-Jan-2017

  72. Yang Hu, Alan J. Curran, Rojiar Haddadian, Timothy J. Peshek, and Roger H. French, “Month-by-Month Analysis of the Power Change Rate of Real World, Outdoor, Photovoltaic Systems Across Multiple Climate Zones,” presented at the NREL PV Reliability Workshop, 360 Union Blvd, Lakewood, CO 80228, 28-Feb-2017

  73. Y. Wang et al., “Model development of degradation of PV modules backsheet with locating place of module,” presented at the Reliability of Photovoltaic Cells, Modules, Components, and Systems X, 2017, vol. 10370, p. 103700L

  74. A. Verma, J. Hawk, L. S. BRUCKMAN, V. Romanov, R. H. FRENCH, and J. Carter, “Application of Data Science to the Study and Design of 9-12% Cr steel,” presented at the Research ShowCASE, Cleveland, OH USA, 21-Apr-2017

  75. Shreyas M. Kamath, “EDIFES (Energy Diagnostics Investigator for Efficiency Savings) Project,” presented at the 3rd Annual Data and Life Science Collaboration and Symposium, 10-Jul-2017.

  76. V. Romanov et al., “Use of Data Analytics in Advanced Alloy Development: Trends and Modeling,” presented at the Crosscutting Research, Pittsburgh, PA, 21-Mar-2017.

  77. Rojiar Haddadian, Yang Hu, Alan J. Curran, Timothy J. Peshek, and Roger H. French, “Temporal Changes in the Power Production of Real-World Photovoltaic Systems Under Diverse Climatic Conditions,” presented at the Joint Statistical Meeting 17, Washington, D.C., Jul-2017

  78. Mohammad Akram Hossain Arash Khalilnejad, “Data Analytics for Building Energy Audits,” presented at the Cyber Infrastructure, Tinkham, 07-Apr-2017

  79. Li, N. Tietsort, A. Joselson, Y. Sheng, R. French, and L. Bruckman, “The Predictive semi-gSEM Models of Waterborne Acrylic Coatings under multi-factor Accelerated Weathering Test,” presented at the MRS Spring 2017, Phoenix, AZ, 19-Apr-2017

  80. Li Donghui, Laura Bruckman, French Roger, Tietsort Noah, and Joselson Adam, “Predictive Models of the Waterborne Acrylic Coating Degradation under Multifactor Accelerated Weathering Test,” presented at the 2017 CoaingsTech Conference, Cleveland, OH, 03-Mar-2017

  81. Kevin Nash, “EDIFES: Energy Diagnostics Investigator for Energy Saving Automated data cleaning for large building energy consumption time series dataset,” presented at the 3rd Annual Data and Life Science Collaboration and Symposium, 10-Jul-2017

  82. Justin S. Fada, Mohammad A. Hossain, Nicholas R. Wheeler, Timothy J. Peshek, and Roger H. French, “Employing Image Processing and Statistical Learning Methodologies to Classify Degradation Feature Types in Electroluminescent Images,” CWRU, Cleveland OH, Jan-2017.

  83. Justin S. Fada, Mohammad A. Hossain, Jennifer L. Braid, Timothy J. Peshek, and Roger H. French, “Machine Learning Classification of PV Cell Degradation Modes in Electroluminescent Images and Cross-Correlation with I-V Curve Parameters,” presented at the CWRU/Tohoku University Data Science Symposium in Life Sciences and Engineering 2017, Case Western Reserve University, Cleveland OH, Aug-2017

  84. Justin S. Fada et al., “Correlation of I-V Curve Parameters with Module-Level Electroluminescent Image Data Over 3000 Hours Damp-Heat Exposure,” WASHINGTON, D.C., 25-Jun-2017

  85. Hanke Gu, Celeste Cooper, Roger H. French, and Mark R. De Guire, “Data Science and Analytics Applied to SOFC Durability Time-series Datasets,” presented at the DOE Solid State Energy Conversion Alliance (SECA)June Meeting, 09-May-2017

  86. D. Gordon, “Multivariate Multiple Regression Models of Poly(ethylene-terephthalate) Film Degradation Under Real World and Multi-Stressor Accelerated Weathering Exposures,” presented at the 3rd Annual Data and Life Sciences Collaboration and Symposium, Cleveland, OH USA, 04-Aug-2017.

  87. Gabriel S. Carrillo, “Quantifying the Contact Boundary Velocity Between an Indenter and a Biologically-Inspired Adhesive Polydimethylsiloxane using Automated Video Analysis Techniques,” presented at the 3rd Annual Data and Life Science Collaboration and Symposium, 03-Aug-2017.

  88. J. S. Fada et al., “Correlation of I-V Curve Parameters with Module-Level Electroluminescent Image Data Over 3000 Hours Damp-Heat Exposure,” Washington, D.C., 2017.

  89. J. S. Fada, M. A. Hossain, N. Wheeler, T. Peshek, and R. French, “Characterization of Photovoltaic Cell Degradation Types using Statistical Learning Methods,” presented at the CWRU Cyberinfrastructure Day, Cleveland, OH USA, 06-Apr-2017.

  90. J. S. Fada, M. A. Hossain, J. L. Braid, S. Yang, T. J. Peshek, and R. H. French, “Electroluminescent Image Processing and Cell Degradation Type Classification via Computer Vision and Statistical Learning Methodologies,” Washington, D.C., 25-Jun-2017.

  91. J. S. Fada, M. A. Hossain, J. L. Braid, S. Yang, T. J. Peshek, and R. H. French, “Electroluminescent Image Processing and Cell Degradation Type Classification via Computer Vision and Statistical Learning Methodologies,” Washington, D.C., 2017.

  92. J. S. Fada, “Analysis of Photovoltaic Module Degradation using Current – Voltage (I-V) Curve Tracing,” presented at the CWRU Research ShowCASE, CWRU, Cleveland OH, 27-Apr-2017.

  93. J. S. Fada, “Electroluminescent Image Processing and Cell Degradation Type Classification via Computer Vision and Statistical Learning Methodologies,” presented at the CWRU Research ShowCASE, CWRU, Cleveland OH, 21-Apr-2017 

  94. Devin A. Gordon et al., “Characterizing the Weathering Induced Changes in the Optical Performance and Properties of Poly(ethylene-terephthalate) via MaPd:RTS Spectroscopy,” presented at the SPIE Optics + Photonics for Sustainable Energy, San Diego, CA, USA, 06-Aug-2017

  95. A. J. Curran et al., “Determining the Power Rate of Change of 353 Solar Plant Inverters Using a Month-by-Month Analysis and Common Data Science Applications to Power Time Series,” presented at the Tohoku Data Symposium, CWRU, 03-Aug-2017.

  96. C. Birk Jones et al., “Quantify PV Module Degradation based on Model Coefficients Extracted from an Embedded Data Acquisition Devices,” presented at the IEEE PVSC 44, Washington, D.C., 2017.

  97. C. Birk Jones et al., “Quantify PV Module Degradation based on Model Coefficients Extracted from an Embedded Data Acquisition Devices,” Washington, D.C., 2017

  98. J. L. Braid, J. S. Fada, T. D. Wager, and X. Ma, “Insights into PERC Cell and Module Lifetime Performance From Modeling I-V, Suns-Voc, and Advanced Characterization Data,” presented at the PVPMC-9, Weihai, China, 06-Dec-2017

  99. Arash Khalilnejad, “EDIFES (Energy Diagnostics Investigator for Efficiency Savings) Forecast energy consumption using diffusion index,” presented at the 3rd Annual Data and Life Science Collaboration and Symposium, 10-Jul-2017.

  100. Arash Khalilnejad, “EDIFES: Energy Diagnostics Investigator for Efficiency Savings  Building Energy Data Pre-processing,” presented at the ARPA-E, Washington DC, Maryland, 2017

  101. Andrew J. Loach, “Quantitative Video and Image Processing of Surface Crystallization of Magnetically Levitated Alloys,” presented at the 3rd Annual Data and Life Science Collaboration and Symposium, 03-Aug-2017

  102. Alan J. Curran, Yang Hu, Rojiar Haddadian, David Meakin, Timothy J. Peshek, and Roger H. French, “Determining the Power Change Rate of 373 Plant Inverter’s Time-series Data Across Multiple Climate Zones, Using a Month-by-Month Data Science Analysis,” 2660 Woodley Road NW Washington, District Of Columbia 20008 USA, 2017.

  103. Alan J. Curran, Yang Hu, Rojiar Haddadian, Timothy J Peshek, and Roger H French, “Month-by-Month Analysis of the Power Change Rate of Real World Photovoltaic Systems Across Multiple Climate Zones,” presented at the CWRU Research showCASE, CWRU Research showCASE, Apr-2017.

  104. Alan J. Curran et al., “Module Level Exposure and Evaluation Test (MLEET) for Real-World & Laboratory-Based PV Modules: Common Data and Analytics for Quantitative Cross-Correlation and Validation,” presented at the Department of Energy SunShot Poster Crawl, Jun-2017.

  105. Alan J. Curran, Ahmad Maroof Karimi, Yang Hu, Rojiar Haddadian, Timothy J. Peshek, and Roger H. French, “Month-by-Month Analysis of the Power Change Rate of RealWorld, Outdoor, Photovoltaic Systems Across Multiple ClimateZones,” presented at the CWRU Cyberinfrastructure Day, Apr-2017.

  106. Alan J. Curran, Ahmad Maroof Karimi, Kevin J. Nash, JiQi Liu, Yang Hu, and Roger H. French, “Rate Of Change Determination Of Real-world Commercial PV Power Plants using Data-driven Modeling,” 05-Oct-2017 

  107. Ahmad Maroof Karimi et al., “E-CRADLE’s Scalable Computing Infrastructure For Large Scale Advanced Computational Analytics,” presented at the CWRU/Tohoku University Data Science Symposium in Life Sciences and Engineering 2017, Case Western Reserve University, Cleveland OH, Aug-2017.

  108. Ahmad Maroof Karimi et al., “Energy-CRADLE: A Scalable Infrastructure For Large Scale Distributed Database & Computational Analytics,” NSF Midwest Big Data Hub, Omaha, Nebraska, Jun-2017.

  109. Addison Klinke, Abdulkerim Gok, Roger H. French, and Laura S. Bruckman, “Comparison of PV Module Backsheet Materials Under Multi-Factor Accelerated UV Light Exposures,” San Diego, CA, 2017

  110. A. J. Curran et al., “Classification of PV System Power Change Rates Using the Month-by-Month Method and the Köppen-Geiger Climate Zone Schema,” 08-Mar-2017

  111. Y. Wang et al., “Model development of degradation of PV modules backsheet with locating place of module,” presented at the Reliability of Photovoltaic Cells, Modules, Components, and Systems X, 2017, vol. 10370, p. 103700L

  112. A. G. Klinke, A. Gok, S. I. Ifeanyi, R. H. French, and L. S. Bruckman, “Degradation of photovoltaic backsheet materials under multi-factor accelerated UV light exposures,” presented at the Reliability of Photovoltaic Cells, Modules, Components, and Systems X, 2017, vol. 10370, p. 1037004

  113. D. A. Gordon et al., “Characterizing the weathering induced changes in optical performance and properties of poly(ethylene-terephthalate) via MaPd:RTS spectroscopy,” presented at the Reliability of Photovoltaic Cells, Modules, Components, and Systems X, 2017, vol. 10370, p. 1037005

  114. A. Fairbrother et al., “Degradation analysis of field-exposed photovoltaic modules with non-fluoropolymer-based backsheets,” presented at the Reliability of Photovoltaic Cells, Modules, Components, and Systems X, 2017, vol. 10370, p. 1037003.

  115. J. S. Fada et al., “Correlation of I-V Curve Parameters with Module-Level Electroluminescent Image Data Over 3000 Hours Damp-Heat Exposure,” Washington, D.C., 2017.

  116. J. S. Fada, M. A. Hossain, J. L. Braid, S. Yang, T. J. Peshek, and R. H. French, “Electroluminescent Image Processing and Cell Degradation Type Classification via Computer Vision and Statistical Learning Methodologies,” Washington, D.C., 2017

  117. C. Birk Jones et al., “Quantify PV Module Degradation based on Model Coefficients Extracted from an Embedded Data Acquisition Devices,” Washington, D.C., 2017

  118. J. L. Braid, J. S. Fada, T. D. Wager, and X. Ma, “Insights into PERC Cell and Module Lifetime Performance From Modeling I-V, Suns-Voc, and Advanced Characterization Data,” presented at the PVPMC-9, Weihai, China, 06-Dec-2017

  119. Alan J. Curran, Yang Hu, Rojiar Haddadian, David Meakin, Timothy J. Peshek, and Roger H. French, “Determining the Power Change Rate of 373 Plant Inverter’s Time-series Data Across Multiple Climate Zones, Using a Month-by-Month Data Science Analysis,” 2660 Woodley Road NW Washington, District Of Columbia 20008 USA, 2017.

  120. Addison Klinke, Abdulkerim Gok, Roger H. French, and Laura S. Bruckman, “Comparison of PV Module Backsheet Materials Under Multi-Factor Accelerated UV Light Exposures,” San Diego, CA, 2017 

  121. Yang Hu et al., “A Nonrelational Data Warehouse for the Analysis of Field and Laboratory Data From Multiple Heterogeneous Photovoltaic Test Sites,” IEEE Journal of Photovoltaics, vol. 7, no. 1, pp. 230–236, Jan. 2017.

  122. Yang Hu, Timothy J. Peshek, Rojiar Haddadian, Roger H. French, and Yang Hu, Timothy J. Peshek, Rojiar Haddadian, Roger H. French, “Modeling the Long-term Temporal Change of Power Production for Real-world Photovoltaic Systems,” IET Renewable Power Generation.

  123. Timothy J. Peshek et al., “Self Assembled Small Molecule Modifiers on Cu(InGa)Se2: A Potential Pathway to Long-Lived Thin Film Photovoltaics,” Journal of Photovoltaics, Jun. 2017

  124. E. M. Pickering, M. A. Hossain, J. P. Mousseau, R. A. Swanson, R. H. French, and A. R. Abramson, “A cross-sectional study of the temporal evolution of electricity consumption of six commercial buildings,” PLOS ONE, vol. 12, no. 10, p. e0187129, Oct. 2017

  125. R. Matthews et al., “Organofunctional Silane Modification of Aluminum-Doped Zinc Oxide Surfaces as a Route to Stabilization,” ACS Appl. Mater. Interfaces, vol. 9, no. 20, pp. 17620–17628, May 2017

  126. A. Gok, D. K. Ngendahimana, C. L. Fagerholm, R. H. French, J. Sun, and L. S. Bruckman, “Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures,” PLOS ONE, vol. 12, no. 5, May 2017 

  127. Gunalan K, Howell B, Patriat R, Duchin Y, Sapiro G, Harel N, McIntyre CC.  Pathway selective deep brain stimulation derived from patient-specific models.  International Congress of Parkinson's Disease and Movement Disorders.  2017.  (Poster presentation)

  128. Gunalan K, McIntyre CC.  Biophysical properties of the hyperdirect pathway necessary to match clinical cortical evoked potentials from subthalamic deep brain stimulation.  Society for Neuroscience Annual Meeting.  2017.  (Poster presentation) 

  129. Gunalan K, Howell B, McIntyre CC.  Quantifying activation of the hyperdirect pathway during subthalamic deep brain stimulation.  17th Quadrennial Meeting of the World Society for Stereotactic and Functional Neurosurgery.  2017.  (Oral presentation)

  130. Maling N, Lempka S, McIntyre CC.  Patient-specific model of subthalamic local field potentials recorded from deep brain stimulation electrodes. 17th Quadrennial Meeting of the World Society for Stereotactic and Functional Neurosurgery.  2017.  (Oral presentation)

  131. Bryan Howell, Invited Talk: Models for Deep Brain Stimulation (M-DBS), 5/24/2017, Institut du Cerveau et de la Moelle Epiniere, Paris, France (invited talk)

  132. Bryan Howell, Minnesota Neuromodulation Symposium, 4/12/2017 – 4/13/2017, University of Minnesota, Minneapolis, MN, USA (poster presentation) 

  133. Lee, H.M., Howell, B., Grill, W.M. and Ghovanloo, M., 2017. Stimulation Efficiency with Decaying Exponential Waveforms in a Wirelessly-Powered Switched-Capacitor Discharge Stimulation System. IEEE Transactions on Biomedical Engineering.